Spring Boot

Integrating Spring Boot with Red Hat Integration Service Registry

Integrating Spring Boot with Red Hat Integration Service Registry

Most of the new cloud-native applications and microservices designs are based on event-driven architecture (EDA), responding to real-time information by sending and receiving information about individual events. This kind of architecture relies on asynchronous, non-blocking communication between event producers and consumers through an event streaming backbone such as Red Hat AMQ Streams running on top of Red Hat OpenShift. In scenarios where many different events are being managed, defining a governance model where each event is defined as an API is critical. That way, producers and consumers can produce and consume checked and validated events. We can use a service registry as a datastore for events defined as APIs.

From my field experience working with many clients, I’ve found the most typical architecture consists of the following components:

In this article, you will learn how to easily integrate your Spring Boot applications with Red Hat Integration Service Registry, which is based on the open source Apicurio Registry.

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Spring Boot on Quarkus: Magic or madness?

Spring Boot on Quarkus: Magic or madness?

Quarkus is a Java stack tailored for OpenJDK HotSpot (or OpenJ9 on zSeries) and GraalVM, crafted from optimized Java libraries and standards. It is a good choice for building highly-scalable applications while using lower amounts of CPU and memory resources than other Java frameworks. These applications can be traditional web applications, serverless applications, or even functions as a service.

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Message broker integration made simple with Red Hat Fuse

Message broker integration made simple with Red Hat Fuse

This article presents a sample integration between Red Hat AMQ 7 and IBM MQ, using Red Hat Fuse 7 for the integration. Traditionally, developers have used resource adapters for message bridging with external systems. A resource adapter is a system library that provides connectivity to an enterprise information system (EIS). Similar to how a Java Database Connectivity (JDBC) driver provides connectivity to a database management system, a resource adapter plugs into an application server such as Red Hat JBoss Enterprise Application Platform (JBoss EAP). It then connects the application server, enterprise information system, and the enterprise application.

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Spring Boot to Quarkus migrations and more in Red Hat’s migration toolkit for applications 5.1.0

Spring Boot to Quarkus migrations and more in Red Hat’s migration toolkit for applications 5.1.0

Red Hat’s migration toolkit for applications (previously known as Red Hat Application Migration Toolkit) has reached version 5.1.0. This version includes user interface improvement, the new migration toolkit for applications Operator, and new rules to support development teams migrating from Spring Boot to Quarkus.

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Cloud-native modernization or death? A false dichotomy

Cloud-native modernization or death? A false dichotomy

DevNation Tech Talks are hosted by the Red Hat technologists who create our products. These sessions include real solutions plus code and sample projects to help you get started. In this talk, you’ll learn about cloud-native modernization from Daniel Oh and Burr Sutter.

Are you familiar with the tight coupling of applications with their underlying platform that makes change hard? Or, coupling that creates a lack of scalability, performance, and flexibility for existing applications built with legacy technology? How about the fact that re-architecting applications cannot be done overnight?

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vscode-xml 0.14.0: A more customizable XML extension for VS Code

vscode-xml 0.14.0: A more customizable XML extension for VS Code

Red Hat’s XML extension for Visual Studio Code (VS Code) has improved significantly since the last release. This article is an overview of the most notable updates in the vscode-xml extension 0.14.0 release. Improvements include embedded settings documentation, customizable document outlines, links for seamless XML catalog navigation, and error aggregation for schema validation.

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Build a data streaming pipeline using Kafka Streams and Quarkus

Build a data streaming pipeline using Kafka Streams and Quarkus

In typical data warehousing systems, data is first accumulated and then processed. But with the advent of new technologies, it is now possible to process data as and when it arrives. We call this real-time data processing. In real-time processing, data streams through pipelines; i.e., moving from one system to another. Data gets generated from static sources (like databases) or real-time systems (like transactional applications), and then gets filtered, transformed, and finally stored in a database or pushed to several other systems for further processing. The other systems can then follow the same cycle—i.e., filter, transform, store, or push to other systems.

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Using Spring Cloud Functions with OpenShift Serverless

Using Spring Cloud Functions with OpenShift Serverless

Spring Cloud Functions are yet another interesting option for Java developers when building serverless applications. You have already seen how to build and run applications for Red Hat OpenShift Serverless using Quarkus, but in this article, we talk about how to use Spring Cloud Functions and walk you through those steps. These steps are similar to running any other Spring Boot application with OpenShift Serverless. One of the benefits of building an open hybrid serverless platform is giving developers a choice of programming languages, tools, frameworks, and portability across any environment to run serverless applications. Beyond that, you want to ensure that the developer experience and overall workflow is intuitive and practical, which is what you will learn here.

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